Topology of megagauss magnetic fields and of heat-carrying electrons produced in a high-power laser-solid interaction

The intricate spatial and energy distribution of magnetic fields, self-generated during high power laser irradiation (at Iλ2∼1013-1014W.cm-2.μm2) of a solid target, and of the heat-carrying electron currents, is studied in inertial confinement fusion (ICF) relevant conditions. This is done by comparing proton radiography measurements of the fields to an improved magnetohydrodynamic description that fully takes into account the nonlocality of the heat transport. We show that, in these conditions, magnetic fields are rapidly advected radially along the target surface and compressed over long time scales into the dense parts of the target. As a consequence, the electrons are weakly magnetized in most parts of the plasma flow, and we observe a reemergence of nonlocality which is a crucial effect for a correct description of the energetics of ICF experiments.

The Application of Computational Chemistry and Chemometrics to Developing a Method for Online Monitoring of Polymer Degradation in the Manufacture of Bioresorbable Medical Implants

Bioresorbable polymers such as PLA have an important role to play in the development of temporary implantable medical devices with significant benefits over traditional therapies. However, development of new devices is hindered by high manufacturing costs associated with difficulties in processing the material. A major problem is the lack of insight on material degradation during processing. In this work, a method of quantifying degradation of PLA using IR spectroscopy coupled with computational chemistry and chemometric modeling is examined. It is shown that the method can predict the quantity of degradation products in solid-state samples with reasonably good accuracy, indicating the potential to adapt the method to developing an on-line sensor for monitoring PLA degradation in real-time during processing.

Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

Controlling Surface Topology and Functionality of Electrospun Fibers on the Nanoscale using Amphiphilic Block Copolymers To Direct Mesenchymal Progenitor Cell Adhesion

Surface patterning in three dimensions is of great importance in biomaterials design for controlling cell behavior. A facile one-step functionalization of biodegradable PDLLA fibers using amphiphilic diblock copolymers is demonstrated here to systematically vary the fiber surface composition. The copolymers comprise a hydrophilic poly[oligo(ethylene glycol) methacrylate] (POEGMA), poly[(2-methacryloyloxy)ethyl phosphorylcholine] (PMPC), or poly[2-(dimethylamino)ethyl methacrylate)] (PDMAEMA) block and a hydrophobic poly(l-lactide) (PLA) block. The block copolymer-modified fibers have increased surface hydrophilicity compared to that of PDLLA fibers. Mixtures of PLAPMPC and PLAPOEGMA copolymers are utilized to exploit microphase separation of the incompatible hydrophilic PMPC and POEGMA blocks at the fiber surface. Conjugation of an RGD cell-adhesive peptide to one hydrophilic block (POEGMA) using thiol-ene chemistry produces fibers with domains of cell-adhesive (POEGMA) and cell-inert (PMPC) sites, mimicking the adhesive properties of the extracellular matrix (ECM). Human mesenchymal progenitor cells (hES-MPs) showed much better adhesion to the fibers with surface-adhesive heterogeneity compared to that to fibers with only adhesive or only inert surface chemistries.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

A combined transient and computational study of the dissociation of N(2)O on platinum catalysts

The energetics of the low-temperature adsorption and decomposition of nitrous oxide, N(2)O, on flat and stepped platinum surfaces were calculated using density-functional theory (DFT). The results show that the preferred adsorption site for N(2)O is an atop site, bound upright via the terminal nitrogen. The molecule is only weakly chemisorbed to the platinum surface. The decomposition barriers on flat (I 11) surfaces and stepped (211) surfaces are similar. While the barrier for N(2)O dissociation is relatively small, the surface rapidly becomes poisoned by adsorbed oxygen. These findings are supported by experimental results of pulsed N(2)O decomposition with 5% Pt/SiO(2) and bismuth-modified Pt/C catalysts. At low temperature, decomposition occurs but self-poisoning by O((ads)) prevents further decomposition. At higher temperatures some desorption Of O(2) is observed, allowing continued catalytic activity. The study with bismuth-modified Pt/C catalysts showed that, although the activation barriers calculated for both terraces and steps were similar, the actual rate was different for the two surfaces. Steps were found experimentally to be more active than terraces and this is attributed to differences in the preexponential term. (C) 2004 Elsevier Inc. All rights reserved.

Burkholderia cenocepacia and Salmonella enterica ArnT proteins that transfer 4-amino-4-deoxy-L-arabinose to lipopolysaccharide share membrane topology and functional amino acids

We recently demonstrated that incorporation of 4-amino-4-deoxy-l-arabinose (l-Ara4N) to the lipid A moiety of lipopolysaccharide (LPS) is required for transport of LPS to the outer membrane and viability of the Gram-negative bacterium Burkholderia cenocepacia. ArnT is a membrane protein catalyzing the transfer of l-Ara4N to the LPS molecule at the periplasmic face of the inner membrane, but its topology and mechanism of action are not well characterized. Here, we elucidate the topology of ArnT and identify key amino acids that likely contribute to its enzymatic function. PEGylation assays using a cysteineless version of ArnT support a model of 13 transmembrane helices and a large C-terminal region exposed to the periplasm. The same topological configuration is proposed for the Salmonella enterica serovar Typhimurium ArnT. Four highly conserved periplasmic residues in B. cenocepacia ArnT, tyrosine-43, lysine-69, arginine-254 and glutamic acid-493, were required for activity. Tyrosine-43 and lysine-69 span two highly conserved motifs, 42RYA44 and 66YFEKP70, that are found in ArnT homologues from other species. The same residues in S. enterica ArnT are also needed for function. We propose these aromatic and charged amino acids participate in either undecaprenyl phosphate-l-Ara4N substrate recognition or transfer of l-Ara4N to the LPS.

Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Motivated by the need for designing efficient and robust fully-distributed computation in highly dynamic networks such as Peer-to-Peer (P2P) networks, we study distributed protocols for constructing and maintaining dynamic network topologies with good expansion properties. Our goal is to maintain a sparse (bounded degree) expander topology despite heavy {\em churn} (i.e., nodes joining and leaving the network continuously over time). We assume that the churn is controlled by an adversary that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is a randomized distributed protocol that guarantees with high probability the maintenance of a {\em constant} degree graph with {\em high expansion} even under {\em continuous high adversarial} churn. Our protocol can tolerate a churn rate of up to $O(n/\poly\log(n))$ per round (where $n$ is the stable network size). Our protocol is efficient, lightweight, and scalable, and it incurs only $O(\poly\log(n))$ overhead for topology maintenance: only polylogarithmic (in $n$) bits needs to be processed and sent by each node per round and any node's computation cost per round is also polylogarithmic. The given protocol is a fundamental ingredient that is needed for the design of efficient fully-distributed algorithms for solving fundamental distributed computing problems such as agreement, leader election, search, and storage in highly dynamic P2P networks and enables fast and scalable algorithms for these problems that can tolerate a large amount of churn.

Fast Byzantine Leader Election in Dynamic Networks

We study the fundamental Byzantine leader election problem in dynamic networks where the topology can change from round to round and nodes can also experience heavy {\em churn} (i.e., nodes can join and leave the network continuously over time). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an $O(\log^3 n)$ round algorithm that achieves Byzantine leader election under the presence of up to $O({n}^{1/2 - \epsilon})$ Byzantine nodes (for a small constant $\epsilon > 0$) and a churn of up to \\$O(\sqrt{n}/\poly\log(n))$ nodes per round (where $n$ is the stable network size).The algorithm elects a leader with probability at least $1-n^{-\Omega(1)}$ and guarantees that it is an honest node with probability at least $1-n^{-\Omega(1)}$; assuming the algorithm succeeds, the leader's identity will be known to a $1-o(1)$ fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in $n$) time and requires nodes to send and receive messages of only polylogarithmic size per round.To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way.We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

DEX: self-healing expanders

Report from the 2nd Summer School in Computational Biology organized by the Queen's University of Belfast

In this paper, we present a meeting report for the 2nd Summer School in Computational Biology organized by the Queen's University of Belfast. We describe the organization of the summer school, its underlying concept and student feedback we received after the completion of the summer school.